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Accurate Conditional Variance Models for Predicting Asymmetric Volatility in Cryptocurrency Markets
Abstract
This study includes tests on the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model and its derivatives to conduct complex and detailed volatility analysis for the 5 highest-volume cryptocurrencies traded in September 2023. The tests have been conducted with Python, R, and Eviews software and analyses have been compared in terms of consistency and accuracy of the results across multiple software and programming languagse. In the testing process, observation of the volatility has been assessed by some variables such as skewness, kurtosis, and log-likelihood values, and these variables have been taken into consideration for testing. Tests such as Jarque-Bera and Augmented Dickey-Fuller (ADF) have been applied during the process to verify model correctness. The EGARCH, GJR-GARCH, and TGARCH models have been more effective in detecting volatility and market shocks in the relevant cryptocurrencies as a result of the tests conducted in the volatility analysis.
Keywords
References
- Anceaume, E., Lajoie-Mazenc, T., Ludinard, R., and Sericola, B. (2016, October). Safety analysis of Bitcoin improvement proposals. In 2016 IEEE 15th International Symposium on Network Computing and Applications (NCA) (pp. 318-325). IEEE.
- Balcilar, M., Gupta, R., and Pierdzioch, C. (2016). Does uncertainty move the gold price? New evidence from a nonparametric causality-in-quantiles test. Resources Policy, 49, 74-80. https://doi.org/10.1016/j.resourpol.2016.04.004
- Bayer, D., Haber, S., and Stornetta, W. S. (1993). Improving the efficiency and reliability of digital time-stamping. In Sequences II: Methods in Communication, Security, and Computer Science (pp. 329-334). Springer New York.
- Beneki, C., Koulis, A., Kyriazis, N. A., and Papadamou, S. (2019). Investigating volatility transmission and hedging properties between Bitcoin and Ethereum. Research in International Business and Finance, 48, 219-227.
- Bera, A. K., and Jarque, C. M. (1982). Model specification tests: A simultaneous approach. Journal of Econometrics, 20(1), 59-82. https://doi.org/10.1016/0304-4076(82)90103-8
- Deavours, C. A., and Kruh, L. (1985). Machine cryptography and modern cryptanalysis. Artech House.
- Chaum, D. (1983, August). Blind signatures for untraceable payments. Advances in Cryptology: Proceedings of Crypto 82 (pp. 199-203). Boston, MA: Springer US.
- Munger, C. T. (2023). Poor Charlie’s Almanack: The essential wit and wisdom of Charles T. Munger. Stripe Press.
Details
Primary Language
English
Subjects
Economic Models and Forecasting, Time-Series Analysis
Journal Section
Research Article
Early Pub Date
November 11, 2024
Publication Date
December 12, 2024
Submission Date
February 8, 2024
Acceptance Date
April 30, 2024
Published in Issue
Year 2024 Volume: 39 Number: 4
APA
Çelebi, O., & Demireli, E. (2024). Accurate Conditional Variance Models for Predicting Asymmetric Volatility in Cryptocurrency Markets. İzmir İktisat Dergisi, 39(4), 909-930. https://doi.org/10.24988/ije.1434189
AMA
1.Çelebi O, Demireli E. Accurate Conditional Variance Models for Predicting Asymmetric Volatility in Cryptocurrency Markets. İzmir İktisat Dergisi. 2024;39(4):909-930. doi:10.24988/ije.1434189
Chicago
Çelebi, Onur, and Erhan Demireli. 2024. “Accurate Conditional Variance Models for Predicting Asymmetric Volatility in Cryptocurrency Markets”. İzmir İktisat Dergisi 39 (4): 909-30. https://doi.org/10.24988/ije.1434189.
EndNote
Çelebi O, Demireli E (December 1, 2024) Accurate Conditional Variance Models for Predicting Asymmetric Volatility in Cryptocurrency Markets. İzmir İktisat Dergisi 39 4 909–930.
IEEE
[1]O. Çelebi and E. Demireli, “Accurate Conditional Variance Models for Predicting Asymmetric Volatility in Cryptocurrency Markets”, İzmir İktisat Dergisi, vol. 39, no. 4, pp. 909–930, Dec. 2024, doi: 10.24988/ije.1434189.
ISNAD
Çelebi, Onur - Demireli, Erhan. “Accurate Conditional Variance Models for Predicting Asymmetric Volatility in Cryptocurrency Markets”. İzmir İktisat Dergisi 39/4 (December 1, 2024): 909-930. https://doi.org/10.24988/ije.1434189.
JAMA
1.Çelebi O, Demireli E. Accurate Conditional Variance Models for Predicting Asymmetric Volatility in Cryptocurrency Markets. İzmir İktisat Dergisi. 2024;39:909–930.
MLA
Çelebi, Onur, and Erhan Demireli. “Accurate Conditional Variance Models for Predicting Asymmetric Volatility in Cryptocurrency Markets”. İzmir İktisat Dergisi, vol. 39, no. 4, Dec. 2024, pp. 909-30, doi:10.24988/ije.1434189.
Vancouver
1.Onur Çelebi, Erhan Demireli. Accurate Conditional Variance Models for Predicting Asymmetric Volatility in Cryptocurrency Markets. İzmir İktisat Dergisi. 2024 Dec. 1;39(4):909-30. doi:10.24988/ije.1434189